Relationships between aquatic biotic communities and water quality in a tropical river–wetland system (Ecuador)

Relationships between aquatic biotic communities and waterquality in a tropical river–wetland system (Ecuador)

G. Alvarez-Mieles a,b,c,*, K. Irvine a, A.V. Griensven a,d, M. Arias-Hidalgo a,b,A. Torres c, A.E. Mynett a,b

aUNESCO-IHE, Institute for Water Education, Department of Water Sciences and Engineering, PO Box 3015,

2601 DA Delft, The NetherlandsbDelft University of Technology, Faculty CiTG, PO Box 5048, 2600 GA Delft, The NetherlandscUniversidad de Guayaquil, Facultad de Ciencias Naturales, Av. Juan Tanca Marengo, Guayaquil, EcuadordVrije Universiteit Brussel, Pleinlaan 2, 1050 Brussel, Belgium

e n v i r o n m e n t a l s c i e n c e & p o l i c y 3 4 ( 2 0 1 3 ) 1 1 5 – 1 2 7

a r t i c l e i n f o

Article history:

Received 10 February 2012

Received in revised form

23 January 2013

Accepted 24 January 2013

Available online 6 March 2013

Keywords:

Aquatic communities

Tropical wetland

Water quality

Bioindicators

Statistical analysis

a b s t r a c t

Many tropical wetlands threatened by land use changes, or modifications in hydrological

regime require effective management policies and implementation to protect them. The

Abras de Mantequilla wetland, located in the Guayas River Basin in Ecuador, is subject to two

major environmental disturbances, i.e., short-term agriculture (rice, maize) on the land

around the wetland and the effects of planned infrastructure works of the Baba dam in the

upper catchment. Both activities are expected to be the main constraints for the future

wetland health. The objective of this study was to provide an initial characterization of the

biotic communities of the river and wetland habitats before the dam starts operating.

Plankton, macroinvertebrates, fishes and associated physical and chemical variables were

sampled at 12 sites during the wet season (February 2011).

Biotic metrics (abundance, taxa richness, diversity and evenness) were computed for the

aquatic communities in the wetland and the river. A biotic index (Biological Monitoring

Working Party-Colombia/adaptation) was applied to the macroinvertebrate community.

Relationships between biotic and abiotic variables indicated nutrients, velocity and sedi-

ment type as main drivers. Cluster analysis grouped physico-chemical variables according

to river or wetland sites. Similarities regarding the taxa composition among sites were

explored with non-metric multidimensional scaling method (NMDS), showing clusters for

ichthyoplankton and macroinvertebrates.

Higher densities of organisms were recorded in the wetland compared with the river. The

wetland is an important area of breeding and reproduction for fish communities, with its

lentic habitats promoting the development of high densities of ichthyoplankton. In order to

achieve sustainable solutions for integrated river–wetland systems, management options

should focus on maintaining natural variation in hydrodynamic conditions throughout the

entire catchment, as well as implement good practices in agriculture and reforestation using

native species. Local and national authorities should support continuous monitoring

programmes, taking account of seasonal variation and of future impacts from flow reduc-

tion and nutrient enrichment.

# 2013 Elsevier Ltd. All rights reserved.

* Corresponding author at: UNESCO-IHE, Institute for Water Education, Department of Water Sciences and Engineering, PO Box 3015, 2601DA Delft, The Netherlands. Tel.: +31 15 2151821; fax: +31 15 2122921.

Available online at www.sciencedirect.com

journal homepage: www.elsevier.com/locate/envsci

E-mail addresses: [email protected], [email protected] (G. Alvarez-Mieles).

1462-9011/$ – see front matter # 2013 Elsevier Ltd. All rights reserved.http://dx.doi.org/10.1016/j.envsci.2013.01.011

e n v i r o n m e n t a l s c i e n c e & p o l i c y 3 4 ( 2 0 1 3 ) 1 1 5 – 1 2 7116

1. Introduction

Wetlands associated with tropical rivers provide valuable

habitats for a diverse and specialized flora and fauna, serve as

important longitudinal and transversal corridors for dispersal

of biota, and provide services at local and catchment scales.

Hydrological, biogeochemical, socioeconomic and ecological

functions of wetlands include water retention, flood control,

water purification and provision of fisheries and forestry

resources. Their ecological significance is expressed in terms

of biodiversity, presence of rare species, habitat and produc-

tivity (Dudgeon et al., 2006; Gopal, 2009; Junk, 2002; Maltby,

2009; Ramsar, 2007).

Increasing impact from a range of pressures on tropical

wetlands include water extraction for irrigation and human

consumption, deforestation, agricultural intensification and

fisheries exploitation. Increasing human populations generate

changes in food production, leading to water deviation and

decreasing wetland area. In severe cases, floodplain wetlands

are drained with the extensive loss of biodiversity and natural

functions. Land use changes affect species diversity and

composition of both plants and animals. The impact of these

activities is still poorly understood (Eppink et al., 2004; Ramsar,

2007).

Preservation of biodiversity in rivers and their associated

riparian areas is related with human society and socioeco-

nomic activities in complex ways (Decamps, 2011; Ramırez

et al., 2008). Wetlands are key elements of a river basin and

wetland management affects river basin services. The

importance of integrating wetlands into river basin manage-

ment has been increasingly recognized (Ramsar, 2007).

However, appropriate monitoring is essential for effective

management. Monitoring programmes require clear objec-

tives, careful selection of measured variables, and a clear

justification for monitoring frequencies (Irvine, 2004, 2009).

Increasingly, biological variables are used in addition to

physical and chemical characteristics. Biological criteria can

represent the status of a river reach or wetland over a longer

period of time than chemical data (Simon, 2000).

The aim of this paper is to evaluate the current ecological

status and the ecological management of the Abras de

Mantequilla wetland in relation to the ongoing and planned

developments in the surrounding river system. This is done by

the assessment of the diversity and abundance of the aquatic

biotic communities and their relationships with abiotic

factors. Such information provides an initial component in

understanding the river–wetland system that can lead to

support wetland stakeholders (local communities, experts and

government authorities) in developing monitoring activities

and environmental management plans for the wetland and

upstream areas.

2. Case study

The Guayas River Basin is located in the Coastal Region

of Ecuador (Los Rıos Province) (Fig. 1). Agriculture, fisheries

and hydropower are the main economic activities in the

basin. Agriculture is based on banana plantations, rice,

maize, African palm and cacao. Two hydro-electrical

projects are located in the upper catchment. These, along

with point and non-point sources of pollution (sewage,

agriculture) and change in land uses are the main environ-

mental pressures.

The Abras de Mantequilla wetland (56000 ha), declared a

RAMSAR site in 2000, is located in the center of Guayas River

Basin. The wetland consists of branching water courses

surrounded by elevations of 5–10 m (Quevedo, 2008). It is part

of the Chojampe sub-basin. Strong interactions between the

wetland and the Nuevo River lead to flooding during the wet

season (January–May), when water depth in the wetland

increases due to the flow of the Nuevo River through Estero

Boqueron (Fig. 1), and when the rainfall run-off from the

Chojampe sub-basin drains into the wetland. The Chojampe

sub-basin contributes approximately 30% of the water, and the

Nuevo River around 70%. During the dry season (July–

November), the water level in the wetland decreases drasti-

cally, and water remains only in the deep central channels,

reducing the inundated area to 10% compared with the wet

season (Arias-Hidalgo et al., 2013).

Current land uses around the wetland and hydropower

projects in the upper catchment are expected to be the main

constraints for the future health of the wetland. The original

forest coverage is less than 3% due to the land conversion to

agriculture in the last decades. Agriculture in the immediate

area of the wetland consists of short term crops (rice, maize)

with intensive use of fertilizers. The Baba hydroelectric

project, located in the upper catchment of Quevedo-Vinces

River started the filling of its reservoir in middle 2011, and is

expected to start operations in 2013. The dam may cause a 43%

reduction in the flow of Vinces River and, consequently, a

decrease in the flow of the Nuevo River (Arias-Hidalgo et al.,

2013).

3. Materials and methods

3.1. Field sampling and laboratory work

Sampling sites were selected according to a spatial distribu-

tion representing the main hydrological features of the

wetland and connected river. Samples were collected from

lentic sites with low velocities (0.1–0.3 m/s), and lotic sites with

velocities >0.5 m/s. Lentic sites (S1, S2, S3b, S3c, S5, S6, S7) are

located in the wetland area. The wetland was divided in three

sections: upper (S5, S6); middle (S1, S2); and low (S7, S3b, S3c).

Lotic sites (S11, S4, S3a) correspond to the inflow (Nuevo River-

Estero Boqueron). S3a is located at the mouth of the wetland

and S11 close to Vinces River. S13 correspond to the outflow

(downstream section of Nuevo River). S9 is located at the North

of the wetland corresponding to the rainfall run-off (drainage

Chojampe sub-basin) (Fig. 1).

A total of 39 physico-chemical variables were measured in

the water column and sediments. Biotic sampling included

phytoplankton, zooplankton, ichthyoplankton, macroinverte-

brates and fishes. The variables were selected to describe a

range of abiotic and biotic characteristics as a first sweep

overview of variables of potential use for long term monitoring

to support management.

Fig. 1 – Location of the sampling sites ‘‘Abras de Mantequilla’’ (AdM) wetland area, Ecuador.

e n v i r o n m e n t a l s c i e n c e & p o l i c y 3 4 ( 2 0 1 3 ) 1 1 5 – 1 2 7 117

Phytoplankton, zooplankton and ichthyoplankton samples

were collected with nets of 55, 200, 300 and 500 mm mesh sizes,

respectively. Horizontal tows of 5 min were performed for

phyto and zooplankton, and 10 min for ichthyoplankton. The

samples were preserved in a 4% formalin solution.

Macro-invertebrates were collected with a hand net of

mesh size 500 mm. In the river, sampling was performed along

the banks. In the wetland, the habitat explored was mainly

floating and emerging vegetation. Each sample was preserved

in 70% alcohol for further analysis. Fishes were sampled at

four sites: three sites in the wetland and one in the connection

point with Estero Boqueron (S3a). Sampling was performed

using a seine net (20 m � 1.5 m, 36 mm mesh size) along the

banks of the wetland, where vegetation was present.

Identification of phytoplankton used a number of keys

(Bourrelly, 1966, 1968, 1970; Desikachary, 1959; Komarek and

Anagnostidis, 2005; Parra et al., 1982; Prescott, 1982). Zoo-

plankton was identified with the keys of Alonso (1996), Brues

et al. (1954), Edmondson (1966), Pennak (1989). For phyto-

plankton quantification, the drip technique of Semina (1978)

was applied. Zooplankton, were counted using sub-samples of

25 ml in a Dolfus chamber (Boltovskoy, 1981). Ichthyoplankton

was enumerated entirely. Macroinvertebrates samples were

analyzed following the procedure recommended by De Pauw

and Vanhooren (1983), consisting of four main steps: sieving

(2000, 1000, 710 and 500 mm), sorting, preservation in 70%

alcohol, and identification with the stereomicroscopic. Iden-

tification was performed to family level with the keys of

Roldan (1996, 2003), with the exception of Anelida and

Arachnida that were identified to class and suborder level,

respectively. Fish identification was performed using taxo-

nomic keys by Eigenmann and Myers (1927), Gerry (1977), Laaz

Table 1 – Physico-chemical variables in water, sediment (sed) and hydraulic variables per sampling sites.

Wetland sites River sites

Variables Units S1 S2 S3b S3c S5 S6 S7 S3a S4 S11 S9 S13 Min* Max*

pH 7.3 6.8 7.0 6.8 6.9 6.9 7.0 7.4 7.2 7.2 6.8 6.7 6.7 7.4

Temperature (8C) 26.4 28.1 24.9 27.3 27.9 25.9 30.7 24.7 25.3 25.3 25.4 25.1 24.7 30.7

Conductivity mS/cm 33.4 33.9 26.0 29.9 21.0 25.7 31.7 29.1 26.4 27.2 30.9 31.5 21.0 33.9

Turbidity NTU 14 3 102 11 256 23 5 117 158 141 19 43 3 256

Hardness mg/CaCO3/l 12.4 14.0 9.3 12.4 9.3 10.1 14.0 10.9 10.9 10.9 10.9 12.4 9.3 14.0

Alkalinity mg/CaCO3/l 48.7 48.7 29.4 38.6 30.5 32.5 44.7 29.4 30.5 30.5 36.5 34.5 29.4 48.7

DO mg/l 1.2 1.7 5.8 3.6 2.2 2.5 5.5 5.7 5.2 5.3 5.2 4.3 1.2 5.8

BOD mg/l 0.2 0.1 0.2 0.1 0.5 0.5 2.2 0.2 0.2 0.4 0.4 0.5 0.1 2.2

COD mg/l 34.3 34.3 34.3 17.1 27.4 68.6 17.1 20.6 17.1 34.3 51.4 17.1 17.1 68.6

TSS mg/l 23 21 80 13 19 16 19 78 29 71 75 24 13 80

TS mg/l 88 70 99 67 53 61 75 102 106 90 90 60 53 106

NO2-N mg/l 0.008 0.004 0.005 0.003 0.009 0.013 0.004 0.006 0.005 0.006 0.008 0.006 0.003 0.013

NO3-N mg/l 0.08 0.05 0.42 0.22 0.35 0.47 0.0002 0.29 0.25 0.46 0.30 0.39 0.0002 0.47

NH4-N mg/l 0.04 0.02 0.02 0.01 0.03 0.04 0.01 0.02 0.01 0.02 0.03 0.03 0.01 0.04

DIN mg/l 0.13 0.07 0.45 0.24 0.38 0.52 0.02 0.31 0.27 0.48 0.34 0.42 0.02 0.52

N_Organic mg/l 0.21 0.23 0.42 0.40 0.39 0.21 0.46 0.45 0.40 0.40 0.39 0.44 0.21 0.46

N_Total mg/l 0.34 0.30 0.87 0.64 0.77 0.73 0.48 0.76 0.67 0.88 0.73 0.87 0.30 0.88

PO4-P mg/l 0.08 0.07 0.02 0.04 0.09 0.10 0.05 0.02 0.02 0.02 0.08 0.03 0.02 0.10

P_Organic mg/l 0.01 0.04 0.05 0.04 0.00 0.00 0.04 0.06 0.05 0.04 0.01 0.03 0.00 0.06

P_Total mg/l 0.09 0.11 0.07 0.08 0.09 0.10 0.09 0.07 0.07 0.06 0.09 0.06 0.06 0.11

SiO4 mg/l 34.9 37.8 41.3 37.7 23.7 28.4 31.8 28.5 35.4 34.1 42.3 35.4 23.7 42.3

SiO4-Si mg/l 10.7 11.5 12.6 11.5 7.2 8.7 9.7 8.7 10.8 10.4 12.9 10.8 7.2 12.9

Organic carbon mg/l 2.2 2.2 7.8 1.8 4.0 5.0 3.4 7.0 8.1 7.8 8.6 3.3 1.8 8.6

Chlorides mg/l 2.9 2.9 3.9 3.9 5.9 6.9 3.9 3.9 3.9 3.9 3.9 4.9 2.9 6.9

Sulfates mg/l 2.3 0.8 10.5 1.1 4.0 3.7 0.9 8.5 8.3 8.1 1.5 1.1 0.8 10.5

Sulphides mg/l 0.2 0.1 0.2 0.2 0.1 0.2 0.1 0.2 0.2 0.2 0.1 0.1 0.1 0.2

Chlorophyll_a mg/l 1.8 4.7 0.6 8.3 0.9 0.8 4.5 1.2 0.5 0.3 1.0 1.9 0.3 8.3

Secchi m 0.9 1.4 0.2 1.1 0.7 0.65 1.1 0.2 0.2 0.2 1 0.2 0.2 1.4

Width m 144 270 332 447 80 102 334 48 24 25 20 35 20 447

Velocity m/s 0.3 0.2 0.6 0.4 0.05 0.3 0.4 0.8 0.8 0.54 0.4 0.5 0.1 0.8

Sulphides(sed) mg/kg 1.6 1.6 2.2 4.4 2.4 1.6 1.6 4 1.6 1.6 1.6 4.4

Sand % 11.2 20.9 38.7 21.6 13.0 29.4 19.0 99.5 99.3 26.0 11.2 99.5

Silt % 32.3 48.7 44.9 49.0 30.6 49.0 47.6 0.4 0.4 49.6 0.4 49.6

Clay % 56.4 30.4 16.4 29.4 56.4 21.56 33.4 0.1 0.1 24.4 0.1 56.4

NO2-N (sed) mg/kg 0.006 0.005 0.002 0.001 0.004 0.003 0.002 0.001 0.003 0.003 0.001 0.006

NO3-N (sed) mg/kg 0.02 0.01 0.01 0.01 0.01 0.002 0.01 0.01 0.01 0.01 0.002 0.02

NH4-N (sed) mg/kg 0.18 0.75 0.41 0.41 0.48 0.61 0.80 0.28 0.27 0.27 0.18 0.80

DIN (sed) mg/kg 0.2 0.8 0.4 0.4 0.5 0.6 0.8 0.3 0.3 0.3 0.2 0.8

N_organic (sed) mg/kg 1.0 0.3 1.9 1.8 0.8 0.9 0.4 1.8 1.6 2.1 0.3 2.1

N_Total (sed) mg/kg 1.2 1.1 2.3 2.2 1.3 1.5 1.2 2.1 1.9 2.4 1.1 2.4

PO4-P (sed) mg/kg 0.15 0.19 0.04 0.01 0.12 0.15 0.07 0.02 0.04 0.08 0.01 0.19

P_organic (sed) mg/kg 0.18 0.37 0.17 0.15 0.29 0.31 0.32 0.05 0.05 0.13 0.05 0.37

P_Total (sed) mg/kg 0.33 0.56 0.21 0.17 0.41 0.45 0.40 0.07 0.09 0.21 0.07 0.56

Organic matter (sed) % 13.8 25.1 13.1 17.4 19.3 14.0 18.1 1.7 1.5 14.0 1.5 25.1

Carbonates (sed) % 0.5 0.5 0.6 0.5 0.6 1.2 0.6 0.5 0.5 0.6 0.5 1.2

Organic carbon (sed) % 6.3 7.6 5.8 7.0 7.2 5.6 7.4 0.8 0.7 5.8 0.7 7.6

COD (sed) mg/kg 195 327 367 273 237 208 417 198 250 253 195 417

* Minimum and Maximum values recorded at all sampling sites.

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e n v i r o n m e n t a l s c i e n c e & p o l i c y 3 4 ( 2 0 1 3 ) 1 1 5 – 1 2 7 119

et al. (2009), Maldonado-Ocampo et al. (2005). Water and

sediment samples were analyzed following the Standard

Methods procedures.

3.2. Data analysis

Estimates of abundance, taxa richness, diversity (Shannon’s

index) and evenness were made for plankton, macroinverte-

brates and fish. A biotic index (Biological Monitoring Working

Party-Colombia/adaptation) (BMWP/Col) was applied to the

macroinvertebrate community (Roldan, 2003). This index is

suitable for application in Ecuador because of presence of

similar taxa (Alvarez, 2007; Dominguez, 2007; VandenBossche,

2009). The index allows grouping the sites into four water

quality classes (WQC): good (I), acceptable (II), doubtful (III) and

critical (IV) (Fig. 4).

Statistical analysis was performed using the statistical

software R version 2.11.1. Analysis of variance (One-way

ANOVA) was applied to analyze differences among BMWP/

Colombia (WQC) in association with physico-chemical and

biotic variables. Pearson correlation method was applied to

explore relationships between abiotic (physico-chemical and

hydraulic) and biotic (single metrics) variables.

Non-metric multidimensional scaling (NMDS) was

applied to visualize the similarities of plankton and

Fig. 2 – Planktonic groups: taxa composition (wetland and

macroinvertebrates taxa composition among the different

sampling sites. The method, based on Bray–Curtis dissimilari-

ty matrices, was calculated from the relative taxa abundances

of each group. From this visual analysis, clusters can be

defined (Anderson, 2006; Dominguez, 2007; Minaya, 2010).

Non-parametric permutational Manova (Permanova) was

applied to determine differences in location and dispersion

among sites. For all statistical analysis, the level of significance

was set at 0.05.

4. Results

4.1. Abiotic variables

The water quality and sediment results from this study are

presented in Table 1. Temperature ranged from 24.7 to 30.7 8C

and dissolved oxygen (DO) between 1.2 and 5.8 mg/l. Low DO

concentrations were registered in wetland sites (S1, S2, S5, S6)

attributed to organic matter decomposition. pH was circum-

neutral (6.7–7.4). Total suspended solids (TSS) ranged between

13 and 80 mg/l, with higher values in river sites because of

higher flow velocities. Conductivity varied between 21 and

34 mS/cm. Nutrients (N, P) were recorded at low concentra-

tions; DIN (sum of: NO2-N; NH4-N; NO3-N) between 0.02 and 0.5

river sites); densities/abundances per sampling sites.

e n v i r o n m e n t a l s c i e n c e & p o l i c y 3 4 ( 2 0 1 3 ) 1 1 5 – 1 2 7120

(mg N/l) with nitrates as the dominant fraction. Total nitrogen

ranged between 0.3 and 0.9 mg/l, and total phosphorus

between 60 and 110 mg/l. Chlorophyll-a concentrations were

between 0.34 and 8.27 mg/l and Secchi depth varied between

0.2 and 1.4 m, with higher values in wetland sites. BOD ranged

between 0.10 and 2.23 mg/l, and COD between 17 and 69 mg/l.

Similar concentrations for these variables have been reported

in the river catchment previously (Efficacitas, 2006; Prado

et al., 2012).

4.2. Biotic variables

4.2.1. Taxa composition and densitiesIn wetland sites, phytoplankton communities were dominated

by diatoms comprising Fragilariophyceae (55%) and Bacilla-

riophyceae (33%). In river sites, Fragillariophyceae dominated

(92%), with Fragilaria longissima as the dominant species in 10

sites. Higher densities of phytoplankton (cells/m3) were

recorded in wetland sites (S5, S6) (Fig. 2).

Zooplankton abundance was higher in wetland sites with

densities up to 14880 org/m3. The community was dominated

by rotifers (57%), with the highest densities in S1, S6, and S7.

Rhizopoda and Cyclopoid copepods were also abundant, with a

share of 24 and 15%, respectively. Copepods also comprised

the highest densities in S1 and S7 (sites that showed the higher

zooplankton densities considering all the taxa). Conversely, in

river sites Rhizopoda was the dominant group (59%) and

Fig. 3 – Macroinvertebrate and fish taxa composition (wetland

Rotifera the second in importance (39%) (Fig. 2). Arcella and

Difflugia, the main species of Rhizopoda, were present in sites

associated with flow that washed out sediments.

Densities of ichthyoplankton were higher in the wetland

sites S2 (705 org/m3) and S7 (482 org/m3), with Engraulidae

(Anchoa sp) as the dominant species (52%). Pre-larval stages

(earlier larval stages which cannot be indentified to taxa)

accounted for 20% and Characidae with different species for

12%. Densities of fish eggs (also a component of ichthyo-

plankton) were highest in the wetland sites, with densities up

to 586 eggs/m3. In river sites, the main groups were Characidae

and Cetopsidae, but larval densities were considerably lower

compared with wetland sites (Fig. 2).

For the macroinvertebrate community, a total of 2087

specimens belonging to 13 orders and 51 families were

collected. In wetland sites, main groups were Amphipoda,

Gastropoda, Coleoptera, Diptera, comprising together about

70% of the total community. In river sites, Diptera was the

dominant group (40%), followed by Ephemeroptera (18%) and

Coleoptera (17%). Wetland Sites S1 and S5 had higher

abundances. Lower densities were recorded from river sites

S4, S9, S11, S13, which could be attributed to higher flow

velocities, suspended solids and less aquatic vegetation

(Fig. 3).

Non-planktonic fish were sampled in four sites, three sites

in the wetland and one in the connection point with Estero

Boqueron (S3a). 22 taxa were identified. Densities ranged from

and river sites); densities/abundances per sampling sites.

Table 2 – Biotic metrics: plankton (phyto, zoo, ichthyoplankton) and macroinvertebrates.

Wetland sites River sites

Biotic metrics Min Max Min Max

BMWP/Colombia 92 178 24 105

ASPT 4.8 5.7 5.3 6.5

Richness phyto 3 24 3 19

Abundance phyto (cell/m3) 6240 778,440 37,440 149,760

Diversity phyto 1.0 2.3 0.3 2.4

Evenness phyto 0.4 1.0 0.3 0.8

Richness zoo 13 29 2 19

Abundance zoo (org/m3) 2884 14,880 6 4049

Diversity zoo 1.0 1.9 0.7 1.2

Evenness zoo 0.4 0.6 0.4 1.0

Richness ichthyo larvae 2 6 1 1

Abundance ichthyo larvae (org/m3) 45 705 5 9

Diversity ichthyo larvae 0.4 1.7 0 0

Abundance ichthyo eggs (org/m3) 27 586 0 5

Richness macro 18 34 4 24

Abundance macro 107 488 8 141

Diversity macro 1.4 2.6 1.1 2.8

Evenness macro 0.5 0.8 0.7 0.9

e n v i r o n m e n t a l s c i e n c e & p o l i c y 3 4 ( 2 0 1 3 ) 1 1 5 – 1 2 7 121

395 to 746 organisms (Fig. 3). Characidae was the representa-

tive family for the fish community. Omnivorous species from

this family, Astyanax festae and Rhoadsia altipinna were the

most abundant in both systems (Fig. 3). Astyanax festae was

abundant in wetland sites where low TSS were found, and

Rhoadsia altipinna, in river site S3a with high concentrations of

TSS and velocities.

4.2.2. Biotic metricsBiotic metrics results are presented in Table 2. All biotic groups

showed higher abundances and species richness in the

wetland than in the river. Densities of ichthyoplankton larvae

and eggs were considerably higher in the wetland.

4.2.3. Biotic indexThe BMWP score (Colombia adaptation) indicated three water

quality classes (WQC) for the study area: Class I (good) in 4 sites

(S1, S3a, S5b, S6); Class II (acceptable) in 4 sites (S2, S4, S5a, S7

and S13), and Class IV (critical) in 2 sites (S9, S11) (Fig. 4). Higher

scores were obtained in the sites with aquatic vegetation,

despite low DO concentrations. Wetland sites S5 and S6 which

contain densely floating vegetation reached a high score,

although they had the lowest DO concentrations of the

sampling sites, while S9 and S11, with DO concentrations

around 5 mg/l, had lower BMWP scores.

4.3. Statistical analysis

From one way ANOVA analysis, only Phytoplankton diversity

and Total suspended solids significantly distinguished the

different BMWP/Col WQC ( p < 0.05). The Critical WQC (IV)

recorded the lowest phytoplankton diversity, and WQC (I) the

highest diversity. The opposite was the case for suspended

solids (Fig. 4).

A summary of significant correlations ( p < 0.05) between

biotic and abiotic variables is presented in the supplementary

file (Appendix A – Table A.1). A number of biotic metrics were

correlated with abiotic variables: nitrogen, phosphorus, total

solids, turbidity, organic matter in sediments and sulphides.

Sediment texture and velocity appeared as the main drivers

for biotic indices. Sites with silt/clay sediments and low flow

velocities (wetland sites) recorded higher number of taxa and

diversities than sites with sandy substrates and high velocities

(river sites). High correlations values were observed among the

biotic indices. Zooplankton and phytoplankton richness were

positively correlated, and their diversity correlated with

BMWP scores.

Non-metric multidimensional scaling of ichthyoplankton

and macroinvertebrates separated the wetland and river sites

(Fig. 5). This was clearest for ichthyoplankton taxa. Clusters

were less distinct for zooplankton and did not seem to occur at

all for phytoplankton.

Clustering of the physical and chemical variables sepa-

rated river and wetland sites clearly (Fig. 6). Nutrient

concentrations were reflected in clusters of wetland (S1,

S2 and S7) and river sites (S3a, S4, S11, S13). Organic

components in sediments formed a representative cluster

(wetland sites). A small cluster is shown for the 2 river sites

(S4, S11). Similarities in concentrations of these 2 sites are

expected as they both are located in the wetland inflow

(Estero Boqueron).

A graphic representation of macroinvertebrate taxa simi-

larities (PERMANOVA: F = 3.5, df1 = 2, p < 0.001) is presented in

Fig. 7. The figure also presents an integrated overview (see

arrows) of phytoplankton abundance, diversity and abiotic

variables (TSS, Nutrients), showing how the river and wetland

systems are ecologically related. Wetland sites (S1, S2, S5, S6)

share similar macroinvertebrate taxa composition with BMWP

water quality classes I and II. Total Nitrogen increased

approaching the wetland inflow (S3a, S11). Total Phosphorus,

however, increased toward the inner wetland sites (S5 and S6).

TSS concentrations below 20 mg/l were recorded in wetland

sites, and between 30 and 80 mg/l in river sites; thus, showing

an increase tendency from wetland to river sites (see isolines).

Phytoplankton abundance and diversity increased from S1

toward S2 and S7 (southern part of the wetland). The

Fig. 4 – (a) BMWP index results per station. (b) Box plots (95% confidence interval) belonging to Phyto_Diversity, and total

suspended solids (TSS) related to the Biological Monitoring Working Party (BMWP/Col (WQC)).

e n v i r o n m e n t a l s c i e n c e & p o l i c y 3 4 ( 2 0 1 3 ) 1 1 5 – 1 2 7122

increasing tendencies of phytoplankton diversity and chloro-

phyll-a are in agreement.

5. Discussion

5.1. Biological and environmental current status

This work provides an initial inventory and assessment of

relationships among biotic and abiotic variables in the Abras

de Mantequilla wetland and river inflow area. Correlation

analysis of biotic and abiotic variables resulted in a better

understanding of the most important environmental factors

influencing species composition and functioning of the river

and wetland ecosystems.

Flow velocity and sediment type were related to the kind of

environment (river or wetland) influencing taxa distribution,

their abundance, richness and diversity. The riverine sites

with sandy substrates and high velocities had lower species

richness and abundance than the wetland sites with fine

particle substrate (silt, clay) and low velocities. Even though

both ecosystems shared some species, mostly because of river

and wetland connectivity, the highest densities and number of

taxa were found in the wetland sites (Figs. 2 and 3), concurring

with Prado et al. (2012).

Cluster analysis for abiotic and biotic variables resulted in

groupings of the wetland and river sites. Such clusters were

observed for ichthyoplankton and macroinvertebrates, sho-

wing their preference for lentic environments with vegetation

availability. Conversely, the overlapping of phytoplankton

suggested the importance of the connection between both

systems for this functional group.

Habitat availability and presence of aquatic plants in the

wetland seemed to be a main driver also for macroinverte-

brates, since the BMWP index classified all wetland sites as

having good and acceptable water quality conditions. Similar

BMWP results in the wetland during the wet season were

reported by VandenBossche (2009).

The dominance of diatoms in the phytoplankton has been

reported previously in the study area (Prado et al., 2009) and in

downstream rivers (Guayas, Daule, Babahoyo) (INP, 1998).

High densities of Fragilaria longissima, also reported by Prado

et al. (2009), have been associated with high concentrations of

dissolved organic matter (Cajas et al., 1998). Rhizopoda with

Arcella and Difflugia dominance were present in wetland and

river sites. These protists are frequent and abundant in rivers

and lakes systems, being reported in other South-American

basins like the Upper Parana River floodplain in Brazil (Mucio

Alves et al., 2010). The dominance of omnivorous fish species

as Astyanax festae is important because they are source of food

for carnivorous fishes (Brycon dentex, Cichlasoma festae) (Laaz

et al., 2009).

Considering the higher densities of ichthyoplankton found

in the wetland sites, Abras de Mantequilla can be considered

as a breeding area for fish that later populate the surrounding

catchment, this is an important ecosystem service. Breeding

occurs mainly in the wet season when the water level is high.

Further analyses with historical data in the study area linked

to flow discharges are recommended to determine optimal

flows for these species.

Fig. 5 – Non-metric multidimensional scaling method (NMS) 2D of the sampling sites using Bray Curtis (dis)similarity on

phyto, zoo, ichthyoplankton, and macroinvertebrates (relative taxa abundances).

e n v i r o n m e n t a l s c i e n c e & p o l i c y 3 4 ( 2 0 1 3 ) 1 1 5 – 1 2 7 123

5.2. Environmental problems

Current stresses in the wetland area are mainly caused by

intensive agriculture. Some associated direct loading of

nutrients from households’ is also likely (Arias-Hidalgo,

2012). Potential future stresses include the activities of the

Baba dam located in the upper section of Vinces River. The

dam will cause a flow reduction, altering natural hydrological

patterns of Nuevo River and, consequently, wetland hydrology

and ecology. A minimum flow (10 m3/s) downstream the Baba

dam was suggested by Efficacitas (2006), after estimations of

the average minimum flows of dry season. Increasing use of

fertilizers combined with this decrease in the Nuevo River

inflow will increase the risk of eutrophication in the wetland.

Nutrient enrichment may lead to high densities of water

hyacinths, negatively affecting several ecosystem services:

navigability, water supply, maintenance of biodiversity,

potential for tourism and recreation.

The majority of wetland biota is adapted to a certain degree

of annual water level change (Gopal, 2009). Timing of the

floods is a main driver for aquatic communities and their

migrations in wetlands. Currently, under natural flow

regimes, the Abras de Mantequilla wetland has a diverse taxa

composition of macroinvertebrates (Fig. 3). Owing to the

projected reduction of flows in Nuevo River, decrease in high

peaks is expected, leading to a shift in biota composition. An

increase in densities of tolerant taxa (some species of Diptera

and Mollusca) that survive in dry and low flow conditions

(O’Keeffe and Dickens, 2000), and a decrease in sensitive

species such as Ephemeroptera could be expected.

Main aspects influencing fish communities are the ones

related to the flood regime (duration, regulation and timing of

the floods and water levels), flooded zone characteristics,

migration routes and availability of refuges during the dry

season (Dugan et al., 2006). These aspects are directly related

to water allocation decisions within the catchment. Main-

taining a near natural flood regime is essential for sustainable

management of the fisheries in the wetland.

5.3. Management options, policy and the role ofbiodiversity

Management options regarding hydraulic, agriculture

and reforestation issues to decrease previously identified

Fig. 6 – Dendrograms for physico-chemical parameters in water and sediment.

e n v i r o n m e n t a l s c i e n c e & p o l i c y 3 4 ( 2 0 1 3 ) 1 1 5 – 1 2 7124

environmental impacts have been proposed (Arias-Hidalgo

et al., 2013). These options include water storage in the

wetland through hydraulic gates, better agriculture practices

(compost and reduction in the use of pesticides), gradual

replacement of short term crops for perennial agroforestry

and increase of ecological corridors. A combination of these

options led to the development of different management

solutions.

A decision support framework has been developed for the

wetland including a set of 19 indicators, including ‘‘Biodiver-

sity (Arias-Hidalgo et al., 2013). Expert judgment was used for

the qualitative assessment of the biodiversity. However, it was

considered as one unit, not distinguishing aquatic or terres-

trial environments. Hence, the need for further elucidation of

biotic structure and interactions is a basic need for the proper

analysis of management options for the wetland.

Biodiversity is considered an environmental service for

local stakeholders, who acknowledged that its conservation

may bring future profits related to ecotourism. Hydrology is a

main driver to sustain wetland biodiversity (Dudgeon et al.,

2006). However, linking biodiversity of aquatic communities

with hydrology and land use management is complex. Despite

its RAMSAR designation, data collection in Abras de Mante-

quilla is at an initial stage. Long term monitoring is essential to

understand the natural variation and response of wetland

biota to hydrology and changes in other pressures. Such

monitoring will assist in developing an effective policy

response to the external pressures that the wetland system

experiment.

We recommend developing a culture of permanent data

collection, supported by national government authorities

(Ministry of Agriculture and Fisheries, Ministry of Environ-

ment, SENAGUA). Monitoring should not be relying only on

ongoing projects that have a limited time frame, or should not

expect fish mortalities. At local management level, the current

legal authority is the commonwealth of the Abras de

Mantequilla wetland municipalities, created in 2008 (Norona,

2009). This body is well placed to raise awareness of the

wetland to the national authorities, and to act as a local

platform integrating interests of policy makers and stake-

holders. Permanent involvement of local dwellers in the

monitoring is important, for instance to set an alarm when a

problem occurs. In this regard continuous capacity building at

local level may prove to be useful.

For monitoring, we recommend maintaining the sampling

sites of this study to have an overview of four main areas in

this river wetland system: upper area (S5 and S6); middle (S1

and S2); downstream (S7, S3b, S3c); inflow (S3a, S4, S11) and

outflow S13. Monitoring should account for seasonality and

therefore be developed at least three times per year during the

wet (January–May), dry season (July–November) and transition

months (June and December). We recommend continuous

monitoring of the biotic communities (phyto, zoo, and

ichthyoplankton), macroinvertebrates and fishes. Based on

Fig. 7 – Macroinvertebrate distribution according to taxa

similarities and the interrelation with biotic and abiotic

variables. Arrows (TSS; nutrients; phytoplankton

abundance and diversity tendencies). Isolines (TSS)

(R: River; W: Wetland). Sites also present the classification

according to the BMWP/WQC (see triangles).

e n v i r o n m e n t a l s c i e n c e & p o l i c y 3 4 ( 2 0 1 3 ) 1 1 5 – 1 2 7 125

the results of physico-chemical variables, monitoring can be

limited to analyze the main abiotic variables: dissolved

oxygen, temperature, Secchi depth, nutrients, chlorophyll-a,

sediment texture and organic matter.

6. Conclusions

Abras de Mantequilla is a valuable wetland that requires

protection against ongoing and planned developments in the

surrounding river basin. Higher densities of organisms were

reported in the wetland compared with the river confirming

its remarkable function as a habitat for aquatic communities.

The study’s results provide quantitative biological informa-

tion for decision support (Arias-Hidalgo et al., 2013). However,

to develop specific eco-hydrological guidelines to maintain

ecosystem health, continuous monitoring supported by

national and local authorities is crucial. Involvement of local

stakeholders increases the legitimacy of management.

Monitoring should be geared to assess (i) natural variations

in hydrodynamic conditions during wet and dry season, (ii)

spatial heterogeneity along the wetland gradient, and (iii)

water quality in the river inflow and wetland. The mainte-

nance of the natural flows from Nuevo River-Estero

Boqueron, especially during the wet season when the

reproduction period occurs will safeguard integrity of the

wetland fish. Reforestation with native species and imple-

mentation of good practices on land use to avoid erosion and

eutrophication provide options to reduce pressures. Joint

efforts of authorities, scientists, and local inhabitants can

make possible the sustainable management of Abras de

Mantequilla wetland.

Acknowledgements

This fieldwork campaign was funded by the WETwin project

(through its Ecuadorian partner CADS-ESPOL), and the

National Institute of Fisheries (INP) in Guayaquil-Ecuador.

The authors thank to INP staff for their cooperation in the

plankton and water quality sampling; Oceanographic Institute

of the Army (INOCAR) for the analysis of chlorophyll-a; Norma

Veloz, Sebastian Alvarado (Guayaquil-University) for the fish

sampling; Andreina Moran, Wilson la-Fuente for the collabo-

ration in macroinvertebrates laboratory work; Professor Piet

Verdonschot from Wageningen-University, for his help in the

identification of macroinvertebrates; Veronica Minaya, for her

important support in the statistical analysis. Finally to local

inhabitants: Telmo Espana, Jimmy Sanchez, Simon Coello for

the transportation and for sharing their valuable local

knowledge.

Appendix A. Supplementary data

Supplementary data associated with this article can be

found, in the online version, at http://dx.doi.org/10.1016/

j.envsci.2013.01.011

r e f e r e n c e s

Alonso, M., 1996. Crustacea, Branchiopoda In: M.A. Ramos, J.A.,X. Belles, J. Gonsalbes, A., Guerra, E., Macpherson, F. Martin& J. Serrano Templado (Ed.), Fauna Iberica Vol 7 (In Spanish).Museo Nacional de Ciencias Naturales-CSIC, Madrid, Spain,p. 486.

Alvarez, G., 2007. Biological indicators, a tool for assessmentof the present state of a river. A pre-impoundment study inthe Quevedo River, Ecuador. Environmental Sciences,UNESCO-IHE, Institute for Water Education, Delft, TheNetherlands, p. 181.

Anderson, M.J., 2006. Distance-based tests for homogeneity ofmultivariate dispersions. Biometrics 62, 245–253.

Arias-Hidalgo, M., 2012. A Decision Framework for integratedwetland-river basin management. In a tropical anddata scarce environment. UNESCO-IHE, Institute forWater Education. PhD thesis, Delft, The Netherlands,p. 180.

Arias-Hidalgo, M., Gonzalo, V.-C., van Griensven, A.,Solorzano, G., Villa-Cox, R., Mynett, A.E., Debels, P., 2013. Adecision framework for wetland management in a riverbasin context: the ‘‘Abras de Mantequilla’’ case study in theGuayas River Basin, Ecuador. Environmental Science andPolicy 34, 103–114.

Boltovskoy, D., 1981 Atlas del Zooplancton del AtlanticoSudoccidental y metodos de trabajo con el zooplanctonmarino (in Spanish), In: Boltovskoy, D. (Ed.). PublicacionEspecial del Instituto Nacional de Investigacion yDesarrollo Pesquero (INIDEP), Mar del Plata, Argentina,p. 1938

Bourrelly P., 1966. Les Algues D’eau Douce. Initiation a laSystematique. Tome I: Les algues Vertes N. Boubee & Cie. ed,Paris.

Bourrelly, P., 1968. Les Algues D’eau Douce. Initiation a laSystematique. Tome II: Les algues jaunes et brunes

e n v i r o n m e n t a l s c i e n c e & p o l i c y 3 4 ( 2 0 1 3 ) 1 1 5 – 1 2 7126

Chrysophycees, Pheophycees, Xanthophycees et Diatomees,N. Boubee & Cie. ed, Paris.

Bourrelly, P., 1970. Les Algues D’eau Douce. Initiation a laSystematique. Tome III: Les algues bleues et rouges LesEugleniens, Peridiniens et Cryptomonadines., N. Boubee &Cie ed, Paris.

Brues, C., Melander, A.L., Carpenter, F.M., 1954. Classification ofinsects. Keys to the Living and Extinct Families of Insects,and to the Living Families of Other Terrestrial Arthropods.In: Bulletin of the Museum of Comparative Zoology, HarvardCollege, Cambridge, MA, USA, p. 916.

Cajas D.L., Prado M., Moya O., 1998. Comunidades delfitoplancton en el Rıo Babahoyo., Comportamiento temporaly espacial de las caracterısticas fısicas, quımicas y biologicasdel Golfo de Guayaquil y sus afluentes Daule y Babahoyoentre 1994–1996 (in Spanish). Instituto Nacional de Pesca,VECEP, Guayaquil Ecuador, pp. 43–57.

De Pauw, N., Vanhooren, G., 1983. Method for biological qualityassessment of watercourses in Belgium. Hydrobiologia 100,153–168.

Decamps, H., 2011. River networks as biodiversity hotlines.Comptes Rendus Biologies 334, 420–434.

Desikachary, T.V., 1959. Cyanophyta. Botany Department –University of Madras, Indian Council of AgriculturalResearch, New Delhi, p. 686.

Dominguez L.E., 2007. Indices based on macroinvertebratecommunities for the assessment of the quality of theChaguana River in Ecuador, PhD thesis. Gent Universiteit,Gent, Belgium.

Dudgeon, D., Arthington, A.H., Gessner, M.O., Kawabata, Z.-I.,Knowler, D.J., Leveque, C., Naiman, R.J., Prieur-Richard, A.-H., Soto, D., Stiassny, M.L.J., Sullivan, C.A., 2006. Freshwaterbiodiversity: importance, threats, status and conservationchallenges. Biological Reviews 81, 163–182.

Dugan, P., Dey, M.M., Sugunan, V.V., 2006. Fisheries and waterproductivity in tropical river basins: enhancing food securityand livelihoods by managing water for fish. AgriculturalWater Management 80, 262–275.

Edmondson, W.T., 1966. Fresh Water Biology, second ed. JohnWiley and Sons, Inc., New York and London.

Efficacitas, 2006. Estudio de Impacto Ambiental Definitivo.Proyecto Multiproposito Baba (in Spanish). ConsorcioHidroenergetico del Litoral. Guayaquil, Ecuador.

Eigenmann, C.H., Myers, G.S., 1927. The American Characidae.Mem Museum of Comparative Zoology, Harvard Cambridge/Mass 43 (5), 429–558.

Eppink, F.V., van den Bergh, J.C.J.M., Rietveld, P., 2004. Modellingbiodiversity and land use: urban growth, agriculture andnature in a wetland area. Ecological Economics 51, 201–216.

Gerry, J., 1977. Characoids of the World. TFH Publications,Neptune, p. 672.

Gopal, B., 2009. Biodiversity in wetlands. In: Maltby, E., Barker,T. (Eds.), The Wetlands Handbook. Wiley-Blackwell, Oxford,UK, pp. 65–95.

INP, 1998. Comportamiento temporal y espacial de lascaracterısticas fısicas, quımicas y biologicas del Golfo deGuayaquil y sus afluentes Daule y Babahoyo (in Spanish).Instituto Nacional de Pesca (INP), Guayaquil, Ecuador.

Irvine, K., 2004. Classifying ecological status under the EuropeanWater Framework Directive: the need for monitoring toaccount for natural variability. Aquatic Conservation:Marine and Freshwater Ecosystems 14, 107–112.

Irvine, K., 2009. Harmonizing assessment of conservation withthat of ecological quality: fitting a square peg into a roundhole? Aquatic Conservation: Marine and FreshwaterEcosystems 19, 365–369.

Junk, W.J., 2002. Long-term environmental trends and thefuture of tropical wetlands. Environmental Conservation 29,414–435.

Komarek, J., Anagnostidis, K., 2005. Cyanoprokaryota 2.Oscillatoriales, Sußwasserflora von Mitteleuropa 19/2(In German), Budel, B., Gartner, G., Krienitz, L. &Schlagerl, M. ed. Elsevier GmbH, Munchen, Germany,p. 760.

Laaz, E., Salazar, V., Torres, A., 2009. Guıa Ilustrada para laidentificacion de peces continentales de la Cuenca del RıoGuayas (in Spanish). Facultad de Ciencias Naturales-Universidad de Guayaquil, Ecuador.

Maldonado-Ocampo, J., Ortega-Lara, A., Usma Oviedo, J., GalvisVergara, G., Villa-Navarro, F., Vasquez Gamboa, L., Prada-Pedreros, S., Ardila Rodrıgues, C., 2005. Peces de Los Andesde Colombia (in Spanish). Instituto de Investigacion deRecursos Biologicos Alexander von Humboldt., Bogota, DC,Colombia.

Maltby, E., 2009. Functional assesment of wetlands. In: TowardsEvaluation of Ecosystem Services, Woodhead PublisingLimited, UK.

Minaya, V., 2010. Land use influence on the benthicmacroinvertebrate communities of streams in Nyangoresand Amala tributaries of Mara River, Kenya, EnvironmentalSciences. UNESCO-IHE, Institute for Water Education, Delft,The Netherlands, p. 97.

Mucio Alves, G., Velho Machado, L.F., Simoes, N.R., Lansac-To ha, F.A., 2010. Biodiversity of testate amoebae (Arcellinidaand Euglyphida) in different habitats of a lake in the UpperParana River floodplain. European Journal of Protistology 46,310–318.

S Norona F B., 2009. Analysis of the decision making processin wetland management and the role of guidelines. CaseStudy: Abras de Mantequilla–Prov. Los Rıos, Ecuador,Water Management. UNESCO-IHE, Delft, The Netherlands,p. 77.

O’Keeffe, J., Dickens, C., 2000. Aquatic invertebrates. In: King,J.M., Tharme, R.E., de Villiers, M.S. (Eds.), Environmentalflow Assessments for Rivers: Manual for the Building BlockMethodology. Water Research Commission, Pretoria, pp.231–244.

Parra, O., Gonzalez, M., Dellarossa, V., Rivera, P., Orellana, M.,1982. Manual taxonomico del fitoplancton de aguascontinentales con especial referencia al fitoplancton de Chile(in Spanish). Universidad de Concepcion, Concepcion, Chile,p. 70.

Pennak, R.W., 1989. Fresh-water Invertebrates of the UnitedStates. Protozoa to Mollusca. Wiley-IntersciencePublications, New York, p. 628.

Prado M., Bucheli R., Calderon G., 2009. Composicion,distribucion y abundancia del plancton en el sistema fluvialde la Provincia de Los Rıos durante el 2009 (in Spanish),Departamento de Investigacion de Recursos Bioacuaticos ysu Ambiente. Instituto Nacional de Pesca (INP). Guayaquil,Ecuador, p. 50.

Prado, M., Revelo, W., Castro, R., Bucheli, R., Calderon, G.,Macıas, P., 2012. Caracterizacion quımica y biologica desistemas hıdricos en la Provincia de Los Rıos-Ecuador (inSpanish). Instituto Nacional de Pesca, Guayaquil, Ecuador, p.100.

Prescott, G.W., 1982. Algae of the Western Great Lakes Area withan Illustrated Key to the Genera of Desmids and FreshwaterDiatoms. Otto Koeltz Science Publishers, Koeningstein,Germany.

Quevedo, O., 2008. Ficha Ramsar del Humedal Abras deMantequilla – Ecuador (in Spanish). Guayaquil,Ecuador.

Ramırez, A., Pringle, C.M., Wantzen, K.M., 2008. Tropical streamconservation. In: David, D. (Ed.), Tropical Stream Ecology.Academic Press, London, pp. 285–304.

Ramsar, C.S., 2007. River basin management: integratingwetland conservation and wise use into river basin

e n v i r o n m e n t a l s c i e n c e & p o l i c y 3 4 ( 2 0 1 3 ) 1 1 5 – 1 2 7 127

management, Ramsar Handbooks for the Wise Use ofWetlands, third ed., vol. 7. Ramsar Convention Secretariat,Gland, Switzerland.

Roldan, G., 1996. Guıa para el estudio de los macroinvertebradosacuaticos del departamento de Antioquia (in Spanish).FENColciencias, Bogota, Colombia.

Roldan, G., 2003. Bioindicacion de la calidad del aguaen Colombia, uso del BMWP/Colombia (in Spanish).FEN-Universidad Antioquia, Medellın,Colombia.

Semina, H.J., 1978. Using the standard microscope. Treatment ofan aliquot sample. In: Sournia, A. (Ed.), PhytoplanktonManual. UNESCO, Paris, p. 344.

Simon, T.P., 2000. The use of biological criteria as a tool forwater resource management. Environmental Science andPolicy 3 (Suppl. 1), 43–49.

VandenBossche, M., 2009. Performance of biological indicesbased on macroinvertebrate communities in the assessmentof the Abras de Mantequilla wetland (Ecuador). GentUniversiteit, Gent, Belgium, p. 94.